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Information Technology 🏢 Full Time ⭐️ Verified

Data Analyst (Weekend Shift) with Relocation Assistance

DataDriven Solutions Inc.
Austin
Estimated Salary
USD 75.000 – USD 95.000
New
Live Update
10 September 2026
Deadline
10 Sep 2027

Job Description

Join DataDriven Solutions Inc. as a Data Analyst on our dynamic weekend shift! We're seeking analytical minds to transform complex datasets into actionable insights while enjoying Austin's vibrant culture. Comprehensive relocation assistance available for qualified candidates moving to the Austin area. Collaborate with cross-functional teams to drive strategic decisions through data storytelling and visualization. Enjoy competitive pay, flexible scheduling, and opportunities for professional growth in one of America's most innovative tech hubs.

Responsibilities

  • Analyze complex datasets to identify trends, patterns, and opportunities for business optimization
  • Create interactive dashboards and reports using tools like Tableau and Power BI
  • Develop SQL queries to extract, clean, and manipulate large datasets
  • Collaborate with stakeholders to define data requirements and deliver actionable insights
  • Monitor key performance indicators (KPIs) and provide weekly analytics summaries
  • Implement data validation protocols to ensure accuracy and reliability
  • Present findings to leadership through compelling visual narratives

Qualifications

  • Bachelor's degree in Data Science, Statistics, Computer Science, or related field
  • 3+ years of experience in data analysis or business intelligence
  • Proficiency in SQL, Python (Pandas, NumPy), and data visualization tools
  • Strong problem-solving skills with attention to detail
  • Experience working with weekend or shift-based schedules
  • Excellent communication skills for translating technical insights to non-technical audiences
  • Ability to manage multiple projects with competing deadlines

Required Skills

SQL Python Tableau Power BI Data Analysis Statistical Modeling Data Visualization Excel ETL Processes

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